Detection of vehicle driver attentiveness is desirable since loss of, or in any way deteriorated, attentiveness impairs the ability of a vehicle to control the vehicle and to be aware of the surroundings. Examples of vehicles are motor vehicles, trains, aircraft and boats. It may also be desirable to detect attentiveness for operators of industrial equipment and the like.
A problem regarding deteriorated attentiveness is that, generally, persons do not detect their own lack of attentiveness when it appears. It is thus difficult for a person to be aware of lack of attentiveness, and to take action for counteraction. Deteriorated attentiveness may be due to different factors such as distracting objects or gadgets as well as drowsiness.
Today, many devices and methods for detecting attentiveness of a vehicle driver are known, and in most cases one or more digital cameras capture images of a vehicle driver's head features and the position of the eyes in order to calculate a gaze angle, and to determine whether the gaze falls within a gaze window. If the calculated gaze angle indicates that the gaze falls outside the gaze window for one or several predetermined amounts of time, it is determined that the driver is inattentive, which result in an alarm and/or other security actions.
Present attentiveness detection systems may use algorithms using advanced generic gaze and headtracking software. Such software creates models of the face which are used to calculate the head and gaze directions. For these models to work, they must track several points on the eyes, nose and mouth. If some of these points are covered or tracked incorrectly, the performance degrades rapidly, leaving present systems fairly unstable. An example of such a system is disclosed in EP 2298155.
There is thus a need for a device and a method for detecting vehicle driver attentiveness which is less complex and more robust than previously known equipment of this kind, and where the risk of false alerts or other types of malfunctions is reduced.